Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Segregation in Fresh Concrete

Segregation in Fresh Concrete

Segregation in fresh concrete is a phenomenon where the components of the concrete mix separate, leading to uneven distribution and compromised structural integrity. This separation typically occurs when concrete is subjected to excessive horizontal movement within forms, or when it is dropped from considerable heights or forced through narrow, winding paths. As a result, heavier coarse aggregate particles settle at the bottom, while lighter, finer materials such as cement and water rise to the...

Gestalt Principles of Perception

Gestalt Principles of Perception

Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

LoRASculpt: Harmonious Low-Rank Adaptation for Multimodal Large Language Models.

IEEE transactions on pattern analysis and machine intelligence·2026

Same author

Towards clinical-level interpretation of dental panoramic radiography using an instance-guided vision-language model.

Nature biomedical engineering·2026

Same author

Systemic immune-inflammation index predicts post-thrombectomy outcomes and reveals a mediating role in the association between neurocardiac stress and prognosis: a multicenter study.

Frontiers in neurology·2026

Same author

Holistic Invariant Retracing for Distortion-Resilient Multi-Modal Learning in Spatial Transcriptomics.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society·2026

Same author

Differentiable Clustering Graph Convolutional Network for Hyperspectral Unmixing: Methodology and Benchmark.

IEEE transactions on neural networks and learning systems·2026

Same author

MUP-SAM: Multi-scale vision mamba UNet prompt generation for SAM in multi-organ medical image segmentation.

Neural networks : the official journal of the International Neural Network Society·2026

Same journal

Relation DETR+: Exploring Explicit Position Relation Prior for Dense Prediction.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

RBF++: Quantifying and Optimizing Reasoning Boundaries across Measurable and Unmeasurable Capabilities for Chain-of-Thought Reasoning.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

CAFE: Cross-View Adaptive Fusion and Cluster Center Enhancement for Robust Multi-View Clustering.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

DIVER: Reinforced Diffusion Breaks Imitation Bottlenecks in End-to-End Autonomous Driving.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

Ethics-Aware Safe Reinforcement Learning for Rare-Event Risk Control in Interactive Urban Driving.

IEEE transactions on pattern analysis and machine intelligence·2026

Same journal

Learning Shape Anchors for Holistic Indoor Scene Understanding.

IEEE transactions on pattern analysis and machine intelligence·2026

See all related articles

Search research articles

Related Experiment Video

Updated: May 31, 2026

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

High-Quality Entity Segmentation and Grounding.

Lu Qi, Yi-Wen Chen, Tao Zhang

IEEE Transactions on Pattern Analysis and Machine Intelligence

|May 29, 2026

Summary

This summary is machine-generated.

We introduce ESG, a novel pipeline for high-quality entity segmentation and grounding. ESG improves mask accuracy and semantic understanding, outperforming existing methods on diverse tasks.

More Related Videos

Automated Analysis of C. elegans Fluorescence Images using SegElegans

Automated Analysis of C. elegans Fluorescence Images using SegElegans

Published on: October 10, 2025

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

Related Experiment Videos

Last Updated: May 31, 2026

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

Published on: August 13, 2014

Automated Analysis of C. elegans Fluorescence Images using SegElegans

Automated Analysis of C. elegans Fluorescence Images using SegElegans

Published on: October 10, 2025

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Automated Segmentation of Cortical Grey Matter from T1-Weighted MRI Images

Published on: January 7, 2019

Area of Science:

Computer Vision
Artificial Intelligence
Machine Learning

Background:

Class-agnostic segmentation is crucial for generalizing object localization to new data.
Existing methods often lack boundary accuracy and semantic understanding.
Human-interaction-assisted image editing benefits from robust segmentation.

Purpose of the Study:

To propose ESG, a pipeline for high-quality entity segmentation and grounding.
To address limitations in mask accuracy and semantic understanding of current methods.
To introduce the EntitySeg dataset for training and evaluation.

Main Methods:

ESG utilizes a two-stage decoupled design with CropFormer for segmentation and GELLA for language-visual grounding.
CropFormer generates high-quality entity segmentation masks.
GELLA performs noun extraction and semantic matching between text and image regions.

Main Results:

ESG demonstrates effectiveness across five tasks: entity segmentation, panoptic segmentation, open-vocabulary segmentation, referring segmentation, and panoptic localized narratives.
The GELLA module shows flexibility by processing masks from any segmentation framework.
The proposed EntitySeg dataset provides high-resolution images and quality annotations.

Conclusions:

ESG achieves high-quality entity segmentation and robust grounding.
The decoupled design preserves mask quality and grounding robustness.
ESG offers a flexible solution for various segmentation and grounding tasks.